This paper discusses an algorithm of color image enhancement that is based on a neuro-dynamical model of the ON-OFF neurons in the human visual system. An appropriate form of this model for color image processing is found and the advantages and disadvantages of this model are also analyzed through the computational simulations. Extensive computations demonstrate that this model can achieve a very good degree of color constancy with the selection of a proper passive decay rate constant. At the same time

the trade-off between image enhancement and the fidelity of chromatic rendition is determined by the space surround constant. This neural system performs well on the enhancement for the natural scenes with complex contexts. However

because this neural system is a model of receptive fields of the ganglion cells in the human retina and still based on“gray-world”assumption

and it fails to handle the violations of the gray-world assumption. It shows that this model is still not comprehensive enough to describe the complex visual system and have some restrictions in practical application. Finally

we discussed the possible future improvement of this model.